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update model card README.md

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+ ---
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+ language:
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+ - mn
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+ license: apache-2.0
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - precision
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+ - recall
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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: mn-bert-base-demo-named-entity
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # mn-bert-base-demo-named-entity
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+
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+ This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1468
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+ - Precision: 0.9092
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+ - Recall: 0.9187
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+ - F1: 0.9139
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+ - Accuracy: 0.9757
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 10
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.172 | 1.0 | 477 | 0.1117 | 0.8614 | 0.8811 | 0.8711 | 0.9662 |
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+ | 0.0846 | 2.0 | 954 | 0.1033 | 0.8748 | 0.8957 | 0.8852 | 0.9698 |
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+ | 0.0562 | 3.0 | 1431 | 0.1005 | 0.8808 | 0.9024 | 0.8915 | 0.9716 |
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+ | 0.0398 | 4.0 | 1908 | 0.1105 | 0.8978 | 0.9073 | 0.9025 | 0.9731 |
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+ | 0.0276 | 5.0 | 2385 | 0.1181 | 0.9031 | 0.9121 | 0.9076 | 0.9740 |
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+ | 0.0204 | 6.0 | 2862 | 0.1309 | 0.9039 | 0.9153 | 0.9096 | 0.9747 |
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+ | 0.0138 | 7.0 | 3339 | 0.1322 | 0.9023 | 0.9132 | 0.9077 | 0.9745 |
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+ | 0.0103 | 8.0 | 3816 | 0.1434 | 0.9071 | 0.9153 | 0.9112 | 0.9748 |
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+ | 0.0071 | 9.0 | 4293 | 0.1458 | 0.9041 | 0.9156 | 0.9098 | 0.9750 |
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+ | 0.0052 | 10.0 | 4770 | 0.1468 | 0.9092 | 0.9187 | 0.9139 | 0.9757 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.28.0
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+ - Pytorch 2.0.0+cu118
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+ - Datasets 2.12.0
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+ - Tokenizers 0.13.3